Confessions of an Architect

Privacy by Design (PbD) Confessions of an Architect Privacy by Design | Time to Take Control Toronto, Canada January 28th, 2011 Jeff Jonas, IBM Distinguished Engineer Chief Scientist, IBM Entity Analytics [email_address]

Background
Early 80’s: Founded Systems Research & Development (SRD), a custom software consultancy
1989 – 2003: Built numerous systems for Las Vegas casinos including a technology known as Non-Obvious Relationship Awareness (NORA)
2005: IBM acquires SRD, now chief scientist of IBM Entity Analytics
Personally architected, designed and deployed +/- 100 systems, a number of which contained multi-billions of transactions describing 100’s of millions of entities
Selected Affiliations:
EPIC, Member, Advisory Board
Privacy International, Member, Advisory Board
Markle Foundation, Member, Task Force on National Security in the Information Age
Senior Associate, Center for Strategic and International Studies (CSIS)

A Late Bloomer to Privacy
1980 – 2001 No clue whatsoever
2001 – 2006 Slowly waking up
2007 – 2011 Today, at best, a student of privacy

A Journey Fraught with Reflection and Rethinking The greater my privacy and civil liberties awareness The greater the number of imperfections appear in the rearview mirror

Katrina – Missing Persons Reunification Project
Information about status of persons quickly end up scattered across countless databases
Over 50 such web sites/organizations were identified as having victim related data
Many people were registered duplicate times in the same database
Many people were registered duplicate times across databases
Many people were registered as missing in one database and found in another database
Connecting found persons previously reported as missing becomes nearly impossible
Too many databases
Constantly changing data

Katrina Reunification Project Statistics
Total data sources 15
Usable records 1,570,000
Unique persons 36,815
Total loved ones reunited >100

Katrina – Missing Persons Reunification Project
Privacy by Design
Contractually authorized to delete all the data after the reunification office completed its work
Hence, a few months later, all collected data and reporting products were deleted
DESTRUCTION OF EVIDENCE!
Data Decommissioning – Destruction of Accountability

“ G2” My Skunk Works Project

G2: Sensemaking on Streams
1) Evaluate new information against previous information … as it arrives.
2) Determine if what is being observing is relevant.
3) Deliver this relevant, actionable insight fast enough to do something about it … as it’s happening.
4) Do this with sufficient accuracy and scale to really matter.

From Pixels to Pictures to Insight Observations Contextualization Information in Context Relevance Consumer (An analyst, a system, the sensor itself, etc.)

G2: Sensemaking on Streams
Domain: People, organizations, places, things, events … proteins, asteroids, and more.
Will simultaneously commingle and make sense over structured, unstructured, biographic, biometric and geospatial data
Multi-lingual
Even curious: If it is unsure, it figures if it is worth researching and may choose to ask Google or maybe even Jeopardy champion to clear up any confusion

Harnessing Big Data. New Physics.
More data: better the predictions
More data: bad data … good
More data: less compute

Smarter Planet: Example G2 Use Cases
Traffic optimization
Route suggestions pushed to drivers, just-in-time, to avert significant traffic events
Optimize individual lives
Search results optimized based on predictions about where you are going next
Pandemic response
A nation able to work right through an extreme global pandemic with real-time citizen recommendations (e.g., “quarantine yourself!”)

THE INFORMATION CONTAINED IN THIS PRESENTATION IS PROVIDED FOR INFORMATIONAL PURPOSES ONLY. ALTHOUGH EFFORTS WERE MADE TO VERIFY THE COMPLETENESS AND ACCURACY OF THE INFORMATION CONTAINED IN THIS PRESENTATION, IT IS PROVIDED “AS IS”, WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED. IN ADDITION, THIS INFORMATION IS BASED ON IBM’S CURRENT PRODUCT PLANS AND STRATEGY, WHICH ARE SUBJECT TO CHANGE BY IBM WITHOUT NOTICE. IBM SHALL NOT BE RESPONSIBLE FOR ANY DAMAGES ARISING OUT OF THE USE OF, OR OTHERWISE RELATED TO, THIS PRESENTATION OR ANY OTHER DOCUMENTATION. NOTHING CONTAINED IN THIS PRESENTATION IS INTENDED TO, OR SHALL HAVE THE EFFECT OF CREATING ANY WARRANTY OR REPRESENTATION FROM IBM (OR ITS AFFILIATES OR ITS OR THEIR SUPPLIERS AND/OR LICENSORS); OR ALTERING THE TERMS AND CONDITIONS OF THE APPLICABLE LICENSE AGREEMENT GOVERNING THE USE OF IBM SOFTWARE.

IBM InfoSphere Sensemaking V1.1.0.0 Following two years of skunk works development while guided by privacy by design goals … it is just possible that there are more privacy and civil liberties enhancing capabilities baked-in, during conception and design, than any other general purpose advanced analytics technology commercially available … on Earth … to date.

PbD: Full Attribution
ABOUT THE FEATURE
Every record knows where it came from and when
No merge/purge data survivorship processing
IMPORTANCE
Universal Declaration of Human Rights has four articles containing the word “arbitrary” e.g., Article 9 reads “ No one shall be subjected to arbitrary arrest, detention or exile.” If you don’t know where the data came from, how can this be non-arbitrary?
The ability to identify every original record is essential for reconciliation and audit

PbD: Data Tethering
ABOUT THE FEATURE
Adds, changes and deletes from source systems can be processed
Real-time, sub-second (not requiring periodic batch reloading)
IMPORTANCE
Data currency in information sharing environments is important e.g., when derogatory data in error is corrected in a source system, it is vital such corrections are corrected everywhere, immediately

PbD: Analytics on Anonymized Data
ABOUT THE FEATURE
Owners of data can anonymize selected fields before an information transfer
Despite the cryptographic form of the data, deep predictive analytics (including some fuzzy matching) can still be accomplished when fusing this data for discovery and analysis
IMPORTANCE
With every copy of data, there is an increased risk of unintended disclosure
Data anonymized before transfer and anonymized at rest reduces the risk of unintended disclosure
And with full attribution, re-identification is by design to ensure reconciliation and audit

PbD: Tamper Resistant Audit Logs
ABOUT THE FEATURE
Who searches for what is logged in a consistent manner
Even the database administrator cannot alter the evidence contained in this log
IMPORTANCE
Every now and then people with access and privileges take a look at records without a legitimate business purpose, e.g., an employee of a banking system looking up their neighbor
Tamper resistant logs make it possible to audit user behavior and can cause chilling-effects on misuse

PbD: False Negative Favoring Methods Patrick T Smith 340-900-9000 Patricia Smith 340-900-9000 Pat T Smith 340-900-9000 Student ? ? 1 2 3 Patrick T Smith 340-900-9000 Patricia Smith 340-900-9000 Pat T Smith 340-900-9000 Student Closest. Hence, for sure EXISTING BEST PRACTICE 1 2 3

PbD: False Negative Favoring Methods
ABOUT THE FEATURE
A false negative occurs when something that is true is not detected
Sometimes a new record can belong to two different entities
Usually systems select the strongest of the two
But had there been only one choice, it would have matched to the other
This is now properly handled, in real-time
IMPORTANCE
If a new record gets arbitrarily assigned, you may have inadvertently created a false positive
False positives can adversely effect peoples lives – e.g., the police find themselves knocking down the wrong door or an innocent passenger is denied the ability to board a plane

PbD: False Negative Favoring Methods NEW BEST PRACTICE Patrick T Smith 340-900-9000 Patricia Smith 340-900-9000 Pat T Smith 340-900-9000 Student 100% 100% Patrick T Smith 340-900-9000 Patricia Smith 340-900-9000 Pat T Smith 340-900-9000 Student ? ? 1 2 3 1 2 3

PbD: Self-Correcting False Positives Which reveals this is a FALSE POSITIVE John T Smith Jr 123 Main Street 703 111-2000 DOB: 03/12/1984 John T Smith 123 Main Street 703 111-2000 DL: 009900991 A plausible claim these two people are the same 1 2 John T Smith Sr 123 Main Street 703 111-2000 DL: 009900991 Until this record comes into view 3

PbD: Self-Correcting False Positives John T Smith Jr 123 Main Street 703 111-2000 DOB: 03/12/1984 John T Smith 123 Main Street 703 111-2000 DL: 009900991 John T Smith Sr 123 Main Street 703 111-2000 DL: 009900991 New Best Practice: FIXED IN REAL-TIME (not end of month) John T Smith 123 Main Street 703 111-2000 DL: 009900991 1 3 2 2

PbD: Self-Correcting False Positives
ABOUT THE FEATURE
A false positive is an assertion (claim) that is made, but not true
With every new data point presented, all prior assertions are re-evaluated to ensure they are still correct, and if now incorrect, these are repaired
If two people were thought to be the same because they share the same name, address and phone – then later it is discovered this is a JR and SR (two different people), this is now remedied
In real-time, not end of month
IMPORTANCE
False positives can adversely effect peoples lives
Without self-correcting false positives, databases start to drift from the truth and become visibly wrong – necessitating periodic reloading to fix this
Periodic monthly reloading would mean wrong decisions are possible all month until the next reload, even though you knew beforehand

PbD: Information Transfer Accounting Basic Data Name: Mark T Smith Address: POB 1346 City: Seattle Phone: (310) 555-0000 Tax ID: 556-99-9999 Balance: $361.43

PbD: Information Transfer Accounting Who Looked Date Name Why 01/09/2010 Ken Wales Teller trans 11/24/2010 Susan Callie Fraud invest

PbD: Information Transfer Accounting Sent Where Date Sent to Why 04/19/2010 ADP Payroll synch 06/01/2010 Amex Marketing alliance 07/16/2010 S&J Inc Third party deal 12/31/2010 IRS Annual compliance

PbD: Information Transfer Accounting
ABOUT THE FEATURE
Can record who inspected each record and record this with the record, mush like a credit report has a list of recent parties who have inquired
Can record what records were transferred to secondary systems, allowing users to inspect information flows
IMPORTANCE
It is often cumbersome to learn who has seen what records or what records have been shared system-to-system
Users can now be easily provided such disclosures increasing transparency and control e.g., able to recall or cancel information transfers from selected sharing partners

A Wide Number of Privacy by Design Features
Data Tethering
Analytics on Anonymized Data
Tamper Resistant Audit Log
Information Transfer Accounting
Full Attribution
False Negative Favoring
Self-Correcting False Positives
By design By design By design By design Mandatory Mandatory Mandatory

IBM InfoSphere Sensemaking V1.1.0.0 Smarter More Responsible &

IBM InfoSphere Sensemaking V1.1.0.0 Challenge Try to find another general purpose advanced analytics technology with more privacy and civil liberties enhancing features baked-in by design! In this competition everyone wins.

And more likeminded, nifty features to come …

IBM InfoSphere Sensemaking V1.1.0.0 Date of availability: January 28th, 2011 ( TODAY! ) ~~ Caveat: Limited availability, subject to lab approval ~~

Related Reference Material
Big Data. New Physics.
Decommissioning Data: Destruction of Accountability
Source Attribution, Don’t Leave Home Without It
Data Tethering: Managing the Echo
Out-bound Record-level Accountability in Information Sharing Systems
To Anonymize or Not Anonymize , That is the Question
Immutable Audit Logs ( IAL’s )
Big Data Flows vs. Wicked Leaks

Privacy-Enhancing Technology, State of the Union
Yesterday: Stand-alone privacy-enhancing technologies
Exist
If cost extra, adoption is low and slow
Some researchers wander off – placing attention elsewhere
Today: Privacy by Design
Baked in
No additional cost
Some privacy and civil liberties enhancing functionality can even be embedded without an off switch

Finally …
Privacy by design is more than just technology.
Equal, if not more attention, must be placed on privacy by design when conceiving process and policy.

Privacy by Design (PbD) Confessions of an Architect Privacy by Design | Time to Take Control Toronto, Canada January 28th, 2011 Jeff Jonas, IBM Distinguished Engineer Chief Scientist, IBM Entity Analytics [email_address]

Confessions of an Architect

by Jeff Jonas

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